Python connects to Alibaba Cloud interface to achieve real-time face recognition and statistics

Python connects to Alibaba Cloud interface to achieve real-time face recognition and statistics

Face recognition technology is widely used in modern society, and with the development of technology, more and more industries are beginning to try to use it applied in actual scenarios. Alibaba Cloud provides a series of face recognition interfaces that can facilitate face recognition and statistics, and the services it provides are stable and reliable, with high accuracy and extremely fast response speed. In this article, we will use Python to connect to the Alibaba Cloud interface to achieve real-time face recognition and statistics, and use actual code examples to explain the specific implementation process.

First, we need to apply for an Access Key ID and Access Key Secret for the face recognition service on the Alibaba Cloud official website, and obtain the corresponding face recognition API service address.

Next, we will use Python’s requests library to send HTTP requests and receive responses. Please make sure you have installed this library, which can be installed through the pip install requests command.

First, we need to import the required libraries:

import requests
import base64
import json

Then, we need to define some necessary parameters, such as Access Key ID, Access Key Secret and the API address of the face recognition service. According to the actual situation, replace it with the value you applied for.

access_key_id = "your-access-key-id"
access_key_secret = "your-access-key-secret"
api_url = "https://api-url"

Next, we need to define a function to send the HTTP request and parse the response. This function will receive an image file path as a parameter and return the results of face detection and recognition.

def face_recognition(image_file):
    # 将图片文件转换为Base64编码的字符串
    with open(image_file, "rb") as f:
        image_data = base64.b64encode(f.read()).decode("ascii")
    
    # 构造请求头部
    headers = {
        "Content-Type": "application/json",
        "Authorization": "APPCODE " + access_key_id + ":" + access_key_secret
    }
    
    # 构造请求体
    body = {
        "image": image_data
    }
    
    # 发送请求
    response = requests.post(api_url, headers=headers, data=json.dumps(body))
    
    # 解析响应
    result = response.json()
    
    # 返回人脸检测和识别的结果
    return result

Finally, we can call this function to achieve real-time face recognition and statistics. Suppose we have a set of face pictures stored in the images folder. We can traverse this folder, perform face recognition on each picture and count the results.

import os

images_dir = "images"
result = {}

# 遍历images文件夹中的所有图片
for filename in os.listdir(images_dir):
    if filename.endswith(".jpg") or filename.endswith(".png"):
        # 拼接图片文件的完整路径
        image_file = os.path.join(images_dir, filename)
        
        # 调用人脸识别函数获取结果
        face_result = face_recognition(image_file)
        
        # 根据识别结果统计
        for face in face_result["faces"]:
            # 获取人脸关键点坐标
            landmark = face["landmark"]
            
            # 统计人脸关键点之和
            key_sum = sum(landmark.values())
            
            # 将结果存放在字典中
            if key_sum in result:
                result[key_sum] += 1
            else:
                result[key_sum] = 1

# 打印统计结果
for key_sum, count in result.items():
    print("人脸关键点之和为{}的数量为{}".format(key_sum, count))

Through the above code examples, we can use Python to connect to the Alibaba Cloud interface to achieve real-time face recognition and statistics. Whether in scenarios such as security systems, face payment, or face attendance, this technology can play an important role. I hope this article can be helpful to you and guide you to further learn and explore the application of face recognition technology.

The above is the detailed content of Python connects to Alibaba Cloud interface to achieve real-time face recognition and statistics. For more information, please follow other related articles on the PHP Chinese website!